Correlation and Regression
ror.br
regression_assignment.xls!REGRESS
| #1. Age (x) | Income (1000s) (y) |
| 27 | 34 |
| 32 | 42 |
| 41 | 37 |
| 35 | 48 |
| 37 | 54 |
| 28 | 32 |
| 31 | 45 |
| 40 | 78 |
| #2 ($ thousands) | |
| Income (x) | Savings (y) |
| 42 | 5 |
| 32 | 3 |
| 27 | 0.5 |
| 31 | 4 |
| 41 | 6 |
| 35 | 5 |
| 37 | 6 |
| 28 | 3 |
| 31 | 2 |
| 40 | 5 |
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Page &p
For each of these,
(a) draw a scatterplot for the two variables
(b) find the correlation coefficient. Discuss its meaning.
(c) find the linear regression equation which predicts y given a value of x. Interpret the meaning of the slope and the y-intercept. For #1, estimate the income of someone who is 32 years old. For #2, estimate the savings of someone who earns $60,000.
